--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/operation_filter.py	Tue Apr 01 10:51:55 2014 -0400
@@ -0,0 +1,99 @@
+# runs after the job (and after the default post-filter)
+import os
+from galaxy import eggs
+from galaxy import jobs
+from galaxy.tools.parameters import DataToolParameter
+
+from galaxy.jobs.handler import JOB_ERROR
+
+# Older py compatibility
+try:
+    set()
+except:
+    from sets import Set as set
+
+#def exec_before_process(app, inp_data, out_data, param_dict, tool=None):
+#    """Sets the name of the data"""
+#    dbkeys = sets.Set( [data.dbkey for data in inp_data.values() ] ) 
+#    if len(dbkeys) != 1:
+#        raise Exception, '<p><font color="yellow">Both Queries must be from the same genome build</font></p>'
+
+def validate_input( trans, error_map, param_values, page_param_map ):
+    dbkeys = set()
+    data_param_names = set()
+    data_params = 0
+    for name, param in page_param_map.iteritems():
+        if isinstance( param, DataToolParameter ):
+            # for each dataset parameter
+            if param_values.get(name, None) != None:
+                dbkeys.add( param_values[name].dbkey )
+                data_params += 1
+                # check meta data
+                try:
+                    param = param_values[name]
+                    if isinstance( param.datatype, trans.app.datatypes_registry.get_datatype_by_extension( 'gff' ).__class__ ):
+                        # TODO: currently cannot validate GFF inputs b/c they are not derived from interval.
+                        pass
+                    else: # Validate interval datatype.
+                        startCol = int( param.metadata.startCol )
+                        endCol = int( param.metadata.endCol )
+                        chromCol = int( param.metadata.chromCol )
+                        if param.metadata.strandCol is not None:
+                            strandCol = int ( param.metadata.strandCol )
+                        else:
+                            strandCol = 0
+                except:
+                    error_msg = "The attributes of this dataset are not properly set. " + \
+                    "Click the pencil icon in the history item to set the chrom, start, end and strand columns."
+                    error_map[name] = error_msg
+            data_param_names.add( name )
+    if len( dbkeys ) > 1:
+        for name in data_param_names:
+            error_map[name] = "All datasets must belong to same genomic build, " \
+                "this dataset is linked to build '%s'" % param_values[name].dbkey
+    if data_params != len(data_param_names):
+        for name in data_param_names:
+            error_map[name] = "A dataset of the appropriate type is required"
+
+# Commented out by INS, 5/30/2007.  What is the PURPOSE of this?
+def exec_after_process(app, inp_data, out_data, param_dict, tool=None, stdout=None, stderr=None):
+    """Verify the output data after each run"""
+    items = out_data.items()
+
+    for name, data in items:
+        try:
+            if stderr and len( stderr ) > 0:
+                raise Exception( stderr )
+
+        except Exception, exc:
+            data.blurb = JOB_ERROR
+            data.state = JOB_ERROR
+
+## def exec_after_process(app, inp_data, out_data, param_dict, tool=None, stdout=None, stderr=None):
+##     pass
+
+
+def exec_after_merge(app, inp_data, out_data, param_dict, tool=None, stdout=None, stderr=None):
+    exec_after_process(
+        app, inp_data, out_data, param_dict, tool=tool, stdout=stdout, stderr=stderr)
+
+    # strip strand column if clusters were merged
+    items = out_data.items()
+    for name, data in items:
+        if param_dict['returntype'] == True:
+            data.metadata.chromCol = 1
+            data.metadata.startCol = 2
+            data.metadata.endCol = 3
+        # merge always clobbers strand
+        data.metadata.strandCol = None
+            
+
+def exec_after_cluster(app, inp_data, out_data, param_dict, tool=None, stdout=None, stderr=None):
+    exec_after_process(
+        app, inp_data, out_data, param_dict, tool=tool, stdout=stdout, stderr=stderr)
+
+    # strip strand column if clusters were merged
+    if param_dict["returntype"] == '1':
+        items = out_data.items()
+        for name, data in items:
+            data.metadata.strandCol = None